The Meaning of Semiochemicals to the Design of Self-Organizing Systems

In biology, many organisms coordinate their interactions in a self-organizing and emergent way solely by means of indirect communication based on chemical substances. These so-called semiochemicals comprise pheromones, mediating the coordination between organisms of the same species, as well as allelochemics, such as allomones, kairomones, synomones, and apneumones, mediating the coordination between organisms of different species. In order to exploit this biological diversity for the engineering of well adapted coordination mechanisms for self-organizing emergent multi-agent systems, the micro- and macroscopic effects of the different types of semiochemicals have to be better understood. In this paper, we analyze these effects and based on that provide design guidelines that identify appropriate types of digital semiochemicals to use for the interactions between agents on the local level in order to achieve certain required effects on the global level. We apply these guidelines within an existing engineering methodology and present as a result an iteratively refined model of a decentralized coordination mechanism well adapted for the solution of pickup and delivery problems by self-organizing emergent multi-agent systems.

[1]  Michael Winikoff,et al.  Developing intelligent agent systems - a practical guide , 2004, Wiley series in agent technology.

[2]  David Hales,et al.  Choose Your Tribe! - Evolution at the Next Level in a Peer-to-Peer Network , 2005, Engineering Self-Organising Systems.

[3]  M. Sol The general pickup and delivery problem , 2010 .

[4]  W. J. Lewis,et al.  Terminology of chemical releasing stimuli in intraspecific and interspecific interactions , 1976, Journal of Chemical Ecology.

[5]  Marco Pistore,et al.  The Tropos Methodology , 2004 .

[6]  R. Whittaker,et al.  Allelochemics: chemical interactions between species. , 1971, Science.

[7]  Franco Zambonelli,et al.  Methodologies and Software Engineering for Agent Systems , 2004, Multiagent Systems, Artificial Societies, and Simulated Organizations.

[8]  Roberto Montemanni,et al.  Design patterns from biology for distributed computing , 2006, TAAS.

[9]  Robert H. Whittaker,et al.  Allomones and Kairomones: Transspecific Chemical Messengers , 1970 .

[10]  E. Morgan,et al.  Insect chemical communication: Pheromones and exocrine glands of ants , 1993, CHEMOECOLOGY.

[11]  W. Z. Lidicker,et al.  A Clarification of Interactions in Ecological Systems , 1979 .

[12]  Ivar Jacobson,et al.  The Unified Software Development Process , 1999 .

[13]  Tom De Wolf,et al.  Towards a Methodology for Engineering Self-Organising Emergent Systems , 2005, SOAS.

[14]  Marco Pistore,et al.  The Tropos Methodology , 2004 .

[15]  Nidhi Kalra,et al.  Market-Based Multirobot Coordination: A Survey and Analysis , 2006, Proceedings of the IEEE.

[16]  Sven A. Brueckner,et al.  RETURN FROM THE ANT SYNTHETIC ECOSYSTEMS FOR MANUFACTURING CONTROL , 2000 .

[17]  Tom De Wolf Analysing and engineering self-organising emergent applications , 2007 .

[18]  Andrea Omicini,et al.  SODA: Societies and Infrastructures in the Analysis and Design of Agent-Based Systems , 2000, AOSE.

[19]  Leon Sterling,et al.  ROADMAP: extending the gaia methodology for complex open systems , 2002, AAMAS '02.

[20]  Andrea Omicini,et al.  Design Patterns for Self-Organizing Multiagent Systems , 2007 .

[21]  Franco Zambonelli,et al.  Field-Based Coordination for Pervasive Multiagent Systems (Springer Series on Agent Technology) , 2005 .

[22]  Tom De Wolf,et al.  A Taxonomy for Self-Properties in Decentralised Autonomic Computing , 2007 .

[23]  T. Meiners,et al.  Rich in phenomena-lacking in terms. A classification of kairomones , 2002, CHEMOECOLOGY.

[24]  Scott A. DeLoach,et al.  Multiagent Systems Engineering , 2001, Int. J. Softw. Eng. Knowl. Eng..

[25]  H. Van Dyke Parunak,et al.  Performance of digital pheromones for swarming vehicle control , 2005, AAMAS '05.

[26]  Franco Zambonelli,et al.  Field-based coordination for pervasive multiagent systems , 2010, Springer series on agent technology.

[27]  Bernhard Bauer,et al.  Pollination - A Biologically Inspired Paradigm for Self-Managing Systems , 2006, Int. Trans. Syst. Sci. Appl..

[28]  Franco Zambonelli,et al.  Towards a paradigm change in computer science and software engineering: a synthesis , 2003, The Knowledge Engineering Review.

[29]  Bernhard Bauer,et al.  Digital Semiochemical Coordination , 2008 .

[30]  Franco Zambonelli,et al.  Challenges and Research Directions in Agent-Oriented Software Engineering , 2004, Autonomous Agents and Multi-Agent Systems.

[31]  Yang Xu,et al.  An integrated token-based algorithm for scalable coordination , 2005, AAMAS '05.

[32]  Sean Luke,et al.  A pheromone-based utility model for collaborative foraging , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..